On: Why Tesla removed radar and ultrasonic sensors [video]

[funstuff007]

> because it's often true that you can deliver better by focusing on a smaller number of things.

This is true / dogma in linear / non-linear regression world, but of no real import in deep learning or Bayesian methods.

[plumefar → funstuff007]

There seem to be 2 points of view here. One technical (sensors and the algorithms), one organisational (people and teams working on the problem).

My understanding is that by focusing on fewer things (vision only), they bet to make progress faster because of the simplified organisational aspect.

[Kerbonut → funstuff007]

I think they’re talking about number of different systems doing the same thing. Have one system doing it that is sufficiently abstracted away from a common set of hardware vs various systems competing for various aspects of control.

[jholman → funstuff007]

Sorry, it's your opinion that researchers and/or engineers working on DL or Bayesian methods work better when they're distracted by many diverse tasks? What?

[funstuff007 → jholman]

No, it's my opinion that in linear regression an inordinate amount of time is spent with feature selection and ensure there's no correlations among the features. When data is cheap in both X and Y, winnowing down X is a lot of work.